Personalized e-course composition approach using digital pheromones in improved particle swarm optimization. - A. P. Sarath Chandar; S. G. Dheeban; Deepak V; Susan Elias (ICNC, 2010)

CDPN: Communicating Dynamic Petri Net for Adaptive Multimedia Presentation. - A. P. Sarath Chandar; S. Arun Balaji; G. Venkatesh; Susan Elias (ICT, 2010)

An Adaptive e-Learning Environment Using Distributed Spiking Neural P Systems. - Susan Elias; A. P. Sarath Chandar; Kamala Krithivasan; S. V. Raghavan (T4E, 2011)

An Autoencoder Approach to Learning Bilingual Word Representations. - A. P. Sarath Chandar; Stanislas Lauly; Hugo Larochelle; Mitesh M. Khapra; Balaraman Ravindran; Vikas C. Raykar; Amrita Saha (NIPS, 2014)

From multiple views to single view: a neural network approach. - Subendhu Rongali; A. P. Sarath Chandar; Balaraman Ravindran (CODS, 2015)

Reasoning about Linguistic Regularities in Word Embeddings using Matrix Manifolds. - Sridhar Mahadevan; Sarath Chandar (CoRR, 2015)

TSEB: More Efficient Thompson Sampling for Policy Learning. - P. Prasanna; Sarath Chandar; Balaraman Ravindran (CoRR, 2015)

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. - Iulian Vlad Serban; Alberto García-Durán; Çaglar Gülçehre; Sungjin Ahn; Sarath Chandar; Aaron C. Courville; Yoshua Bengio (ACL (1), 2016)

A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation. - Amrita Saha; Mitesh M. Khapra; Sarath Chandar; Janarthanan Rajendran; Kyunghyun Cho (COLING, 2016)

Multilingual Multimodal Language Processing Using Neural Networks. - Mitesh M. Khapra; Sarath Chandar (HLT-NAACL Tutorials, 2016)

Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. - Janarthanan Rajendran; Mitesh M. Khapra; Sarath Chandar; Balaraman Ravindran (HLT-NAACL, 2016)

Hierarchical Memory Networks. - Sarath Chandar; Sungjin Ahn; Hugo Larochelle; Pascal Vincent; Gerald Tesauro; Yoshua Bengio (CoRR, 2016)

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (CoRR, 2016)

Correlational Neural Networks. - Sarath Chandar; Mitesh M. Khapra; Hugo Larochelle; Balaraman Ravindran (Neural Comput., 2016)

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. - Harm de Vries; Florian Strub; Sarath Chandar; Olivier Pietquin; Hugo Larochelle; Aaron C. Courville (CVPR, 2017)

Memory Augmented Neural Networks with Wormhole Connections. - Çaglar Gülçehre; Sarath Chandar; Yoshua Bengio (CoRR, 2017)

A Deep Reinforcement Learning Chatbot. - Iulian Vlad Serban; Chinnadhurai Sankar; Mathieu Germain; Saizheng Zhang; Zhouhan Lin; Sandeep Subramanian; Taesup Kim; Michael Pieper; Sarath Chandar; Nan Rosemary Ke; Sai Mudumba; Alexandre de Brébisson; et al. (CoRR, 2017)

Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph. - Amrita Saha; Vardaan Pahuja; Mitesh M. Khapra; Karthik Sankaranarayanan; Sarath Chandar (AAAI, 2018)

A Deep Reinforcement Learning Chatbot (Short Version). - Iulian Vlad Serban; Chinnadhurai Sankar; Mathieu Germain; Saizheng Zhang; Zhouhan Lin; Sandeep Subramanian; Taesup Kim; Michael Pieper; Sarath Chandar; Nan Rosemary Ke; Sai Rajeswar; Alexandre de Brébisson; et al. (CoRR, 2018)

Language Expansion In Text-Based Games. - Ghulam Ahmed Ansari; Sagar J. P; Sarath Chandar; Balaraman Ravindran (CoRR, 2018)

On Training Recurrent Neural Networks for Lifelong Learning. - Shagun Sodhani; Sarath Chandar; Yoshua Bengio (CoRR, 2018)

Environments for Lifelong Reinforcement Learning. - Khimya Khetarpal; Shagun Sodhani; Sarath Chandar; Doina Precup (CoRR, 2018)

Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (Neural Comput., 2018)

Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. - Sarath Chandar; Chinnadhurai Sankar; Eugene Vorontsov; Samira Ebrahimi Kahou; Yoshua Bengio (AAAI, 2019)

Towards Lossless Encoding of Sentences. - Gabriele Prato 001; Mathieu Duchesneau; Sarath Chandar; Alain Tapp (ACL (1), 2019)

Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. - Chinnadhurai Sankar; Sandeep Subramanian; Chris Pal; Sarath Chandar; Yoshua Bengio (ACL (1), 2019)

Structure Learning for Neural Module Networks. - Vardaan Pahuja; Jie Fu 001; Sarath Chandar; Christopher Joseph Pal (LANTERN@EMNLP-IJCNLP, 2019)

Edge Replacement Grammars : A Formal Language Approach for Generating Graphs. - Revanth Reddy; Sarath Chandar; Balaraman Ravindran (SDM, 2019)

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Simon Blackburn; Karam M. J. Thomas; Connor W. Coley; Jian Tang 005; Sarath Chandar; Yoshua Bengio (ICML, 2020)

The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning. - Harm van Seijen; Hadi Nekoei; Evan Racah; Sarath Chandar (NeurIPS, 2020)

The Hanabi challenge: A new frontier for AI research. - Nolan Bard; Jakob N. Foerster; Sarath Chandar; Neil Burch; Marc Lanctot; H. Francis Song; Emilio Parisotto; Vincent Dumoulin; Subhodeep Moitra; Edward Hughes 001; Iain Dunning; Shibl Mourad; et al. (Artif. Intell., 2020)

PatchUp: A Regularization Technique for Convolutional Neural Networks. - Mojtaba Faramarzi; Mohammad Amini; Akilesh Badrinaaraayanan; Vikas Verma; Sarath Chandar (CoRR, 2020)

Slot Contrastive Networks: A Contrastive Approach for Representing Objects. - Evan Racah; Sarath Chandar (CoRR, 2020)

How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics. - Prasanna Parthasarathi; Joelle Pineau; Sarath Chandar (CoRR, 2020)

Maximum Reward Formulation In Reinforcement Learning. - Sai Krishna Gottipati; Yashaswi Pathak; Rohan Nuttall; Sahir; Raviteja Chunduru; Ahmed Touati; Sriram Ganapathi Subramanian; Matthew E. Taylor; Sarath Chandar (CoRR, 2020)

Toward Training Recurrent Neural Networks for Lifelong Learning. - Shagun Sodhani; Sarath Chandar; Yoshua Bengio (Neural Comput., 2020)

Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery. - Sai Krishna Gottipati; Yashaswi Pathak; Boris Sattarov; Sahir; Rohan Nuttall; Mohammad Amini; Matthew E. Taylor; Sarath Chandar (AAAI, 2021)

MLMLM: Link Prediction with Mean Likelihood Masked Language Model. - Louis Clouâtre; Philippe Trempe; Amal Zouaq; Sarath Chandar (ACL/IJCNLP (Findings), 2021)

A Survey of Data Augmentation Approaches for NLP. - Steven Y. Feng; Varun Gangal; Jason Wei; Sarath Chandar; Soroush Vosoughi; Teruko Mitamura; Eduard H. Hovy (ACL/IJCNLP (Findings), 2021)

IIRC: Incremental Implicitly-Refined Classification. - Mohamed A. Abdelsalam; Mojtaba Faramarzi; Shagun Sodhani; Sarath Chandar (CVPR, 2021)

Continuous Coordination As a Realistic Scenario for Lifelong Learning. - Hadi Nekoei; Akilesh Badrinaaraayanan; Aaron C. Courville; Sarath Chandar (ICML, 2021)

A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. - Prasanna Parthasarathi; Mohamed A. Abdelsalam; Sarath Chandar; Joelle Pineau (SIGDIAL, 2021)

Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task ? - Prasanna Parthasarathi; Joelle Pineau; Sarath Chandar (SIGDIAL, 2021)

Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ? - Prasanna Parthasarathi; Joelle Pineau; Sarath Chandar (CoRR, 2021)

Demystifying Neural Language Models' Insensitivity to Word-Order. - Louis Clouâtre; Prasanna Parthasarathi; Amal Zouaq; Sarath Chandar (CoRR, 2021)

Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers. - Gabriele Prato 001; Simon Guiroy; Ethan Caballero; Irina Rish; Sarath Chandar (CoRR, 2021)

PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks. - Mojtaba Faramarzi; Mohammad Amini; Akilesh Badrinaaraayanan; Vikas Verma; Sarath Chandar (AAAI, 2022)

Local Structure Matters Most: Perturbation Study in NLU. - Louis Clouâtre; Prasanna Parthasarathi; Amal Zouaq; Sarath Chandar (ACL (Findings), 2022)

Improving Meta-Learning Generalization with Activation-Based Early-Stopping. - Simon Guiroy; Christopher Pal; Gonçalo Mordido; Sarath Chandar (CoLLAs, 2022)

TAG: Task-based Accumulated Gradients for Lifelong learning. - Pranshu Malviya; Balaraman Ravindran; Sarath Chandar (CoLLAs, 2022)

Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints. - Daphné Lafleur; Sarath Chandar; Gilles Pesant (CP, 2022)

Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes. - Louis Clouâtre; Prasanna Parthasarathi; Amal Zouaq; Sarath Chandar (EMNLP (Findings), 2022)

Memory Augmented Optimizers for Deep Learning. - Paul-Aymeric Martin McRae; Prasanna Parthasarathi; Mido Assran; Sarath Chandar (ICLR, 2022)

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods. - Yi Wan; Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Sarath Chandar; Harm van Seijen (ICML, 2022)

Local Structure Matters Most in Most Languages. - Louis Clouâtre; Prasanna Parthasarathi; Amal Zouaq; Sarath Chandar (AACL/IJCNLP (2), 2022)

Improving Sample Efficiency of Value Based Models Using Attention and Vision Transformers. - Amir Ardalan Kalantari; Mohammad Amini; Sarath Chandar; Doina Precup (CoRR, 2022)

An Introduction to Lifelong Supervised Learning. - Shagun Sodhani; Mojtaba Faramarzi; Sanket Vaibhav Mehta; Pranshu Malviya; Mohamed A. Abdelsalam; Janarthanan Rajendran; Sarath Chandar (CoRR, 2022)

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch? - Enamundram Naga Karthik; Anne Kerbrat; Pierre Labauge; Tobias Granberg; Jason Talbott; Daniel S. Reich; Massimo Filippi; Rohit Bakshi; Virginie Callot; Sarath Chandar; Julien Cohen-Adad (CoRR, 2022)

Sharpness-Aware Training for Accurate Inference on Noisy DNN Accelerators. - Gonçalo Mordido; Sarath Chandar; François Leduc-Primeau (CoRR, 2022)

PatchBlender: A Motion Prior for Video Transformers. - Gabriele Prato 001; Yale Song; Janarthanan Rajendran; R. Devon Hjelm; Neel Joshi; Sarath Chandar (CoRR, 2022)

Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness. - Abdelrahman Zayed; Prasanna Parthasarathi; Gonçalo Mordido; Hamid Palangi; Samira Shabanian; Sarath Chandar (AAAI, 2023)

Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning. - Hadi Nekoei; Akilesh Badrinaaraayanan; Amit Sinha; Mohammad Amini; Janarthanan Rajendran; Aditya Mahajan; Sarath Chandar (CoLLAs, 2023)

Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi. - Hadi Nekoei; Xutong Zhao; Janarthanan Rajendran; Miao Liu; Sarath Chandar (CoLLAs, 2023)

Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning. - Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Harm van Seijen; Sarath Chandar (CoLLAs, 2023)

Measuring the Knowledge Acquisition-Utilization Gap in Pretrained Language Models. - Amirhossein Kazemnejad; Mehdi Rezagholizadeh; Prasanna Parthasarathi; Sarath Chandar (EMNLP (Findings), 2023)

EpiK-Eval: Evaluation for Language Models as Epistemic Models. - Gabriele Prato 001; Jerry Huang; Prasanna Parthasarathi; Shagun Sodhani; Sarath Chandar (EMNLP, 2023)

Self-Influence Guided Data Reweighting for Language Model Pre-training. - Megh Thakkar; Tolga Bolukbasi; Sriram Ganapathy; Shikhar Vashishth; Sarath Chandar; Partha Talukdar (EMNLP, 2023)

Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. - Xutong Zhao; Yangchen Pan; Chenjun Xiao; Sarath Chandar; Janarthanan Rajendran (UAI, 2023)

Replay Buffer With Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning. - Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Harm van Seijen; Sarath Chandar (CoRR, 2023)

Towards Lifelong Learning for Software Analytics Models: Empirical Study on Brown Build and Risk Prediction. - Doriane Olewicki; Sarra Habchi; Mathieu Nayrolles; Mojtaba Faramarzi; Sarath Chandar; Bram Adams (CoRR, 2023)

Should We Attend More or Less? Modulating Attention for Fairness. - Abdelrahman Zayed; Gonçalo Mordido; Samira Shabanian; Sarath Chandar (CoRR, 2023)

Thompson sampling for improved exploration in GFlowNets. - Jarrid Rector-Brooks; Kanika Madan; Moksh Jain; Maksym Korablyov; Cheng-Hao Liu; Sarath Chandar; Nikolay Malkin; Yoshua Bengio (CoRR, 2023)

Lookbehind Optimizer: k steps back, 1 step forward. - Gonçalo Mordido; Pranshu Malviya; Aristide Baratin; Sarath Chandar (CoRR, 2023)

Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games. - Arjun Vaithilingam Sudhakar; Prasanna Parthasarathi; Janarthanan Rajendran; Sarath Chandar (CoRR, 2023)

Post-hoc Interpretability for Neural NLP: A Survey. - Andreas Madsen; Siva Reddy; Sarath Chandar (ACM Comput. Surv., 2023)

An Empirical Investigation of the Role of Pre-training in Lifelong Learning. - Sanket Vaibhav Mehta; Darshan Patil; Sarath Chandar; Emma Strubell (J. Mach. Learn. Res., 2023)

Fairness-Aware Structured Pruning in Transformers. - Abdelrahman Zayed; Gonçalo Mordido; Samira Shabanian; Ioana Baldini; Sarath Chandar (AAAI, 2024)

Are self-explanations from Large Language Models faithful? - Andreas Madsen; Sarath Chandar; Siva Reddy (ACL (Findings), 2024)

A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. - Megh Thakkar; Quentin Fournier; Matthew Riemer; Pin-Yu Chen; Amal Zouaq; Payel Das; Sarath Chandar (ACL (1), 2024)

Why Don't Prompt-Based Fairness Metrics Correlate? - Abdelrahman Zayed; Gonçalo Mordido; Ioana Baldini; Sarath Chandar (ACL (1), 2024)

Sharpness-Aware Minimization Scaled by Outlier Normalization for Robust DNNs on In-Memory Computing Accelerators. - Sébastien Henwood; Gonçalo Mordido; Yvon Savaria; Sarath Chandar; François Leduc-Primeau (IEEECONF, 2024)

MVP: Minimal Viable Phrase for Long Text Understanding. - Louis Clouâtre; Amal Zouaq; Sarath Chandar (LREC/COLING, 2024)

Sub-goal Distillation: A Method to Improve Small Language Agents. - Maryam Hashemzadeh; Elias Stengel-Eskin; Sarath Chandar; Marc-Alexandre Côté (CoLLAs, 2024)

Exploring Quantization for Efficient Pre-Training of Transformer Language Models. - Kamran Chitsaz; Quentin Fournier; Gonçalo Mordido; Sarath Chandar (EMNLP (Findings), 2024)

Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models. - Jerry Huang; Prasanna Parthasarathi; Mehdi Rezagholizadeh; Sarath Chandar (EMNLP, 2024)

Do Large Language Models Know How Much They Know? - Gabriele Prato 001; Jerry Huang; Prasanna Parthasarathi; Shagun Sodhani; Sarath Chandar (EMNLP, 2024)

Intelligent Switching for Reset-Free RL. - Darshan Patil; Janarthanan Rajendran; Glen Berseth; Sarath Chandar (ICLR, 2024)

Mastering Memory Tasks with World Models. - Mohammad Reza Samsami; Artem Zholus; Janarthanan Rajendran; Sarath Chandar (ICLR, 2024)

Faithfulness Measurable Masked Language Models. - Andreas Madsen; Siva Reddy; Sarath Chandar (ICML, 2024)

Lookbehind-SAM: k steps back, 1 step forward. - Gonçalo Mordido; Pranshu Malviya; Aristide Baratin; Sarath Chandar (ICML, 2024)

On the Costs and Benefits of Adopting Lifelong Learning for Software Analytics - Empirical Study on Brown Build and Risk Prediction. - Doriane Olewicki; Sarra Habchi; Mathieu Nayrolles; Mojtaba Faramarzi; Sarath Chandar; Bram Adams (ICSE-SEIP, 2024)

Toward Debugging Deep Reinforcement Learning Programs with RLExplorer. - Rached Bouchoucha; Ahmed Haj Yahmed; Darshan Patil; Janarthanan Rajendran; Amin Nikanjam; Sarath Chandar; Foutse Khomh (ICSME, 2024)

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale. - Matthew Riemer; Khimya Khetarpal; Janarthanan Rajendran; Sarath Chandar (NeurIPS, 2024)

Towards Practical Tool Usage for Continually Learning LLMs. - Jerry Huang; Prasanna Parthasarathi; Mehdi Rezagholizadeh; Sarath Chandar (CoRR, 2024)

Interpretability Needs a New Paradigm. - Andreas Madsen; Himabindu Lakkaraju; Siva Reddy; Sarath Chandar (CoRR, 2024)

Predicting the Impact of Model Expansion through the Minima Manifold: A Loss Landscape Perspective. - Pranshu Malviya; Jerry Huang; Quentin Fournier; Sarath Chandar (CoRR, 2024)

Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs. - Megh Thakkar; Yash More; Quentin Fournier; Matthew Riemer; Pin-Yu Chen; Amal Zouaq; Payel Das; Sarath Chandar (CoRR, 2024)

Too Big to Fool: Resisting Deception in Language Models. - Mohammad Reza Samsami; Mats Leon Richter; Juan A. Rodríguez; Megh Thakkar; Sarath Chandar; Maxime Gasse (CoRR, 2024)

Torque-Aware Momentum. - Pranshu Malviya; Gonçalo Mordido; Aristide Baratin; Reza Babanezhad Harikandeh; Gintare Karolina Dziugaite; Razvan Pascanu; Sarath Chandar (CoRR, 2024)

Promoting Exploration in Memory-Augmented Adam using Critical Momenta. - Pranshu Malviya; Gonçalo Mordido; Aristide Baratin; Reza Babanezhad Harikandeh; Jerry Huang; Simon Lacoste-Julien; Razvan Pascanu; Sarath Chandar (Trans. Mach. Learn. Res., 2024)

BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning. - Artem Zholus; Maksim Kuznetsov; Roman Schutski; Rim Shayakhmetov; Daniil Polykovskiy; Sarath Chandar; Alex Zhavoronkov (AAAI, 2025)

Small Encoders Can Rival Large Decoders in Detecting Groundedness. - Istabrak Abbes; Gabriele Prato 001; Quentin Fournier; Fernando Rodriguez; Alaa Boukhary; Adam Elwood; Sarath Chandar (ACL (Findings), 2025)

Do Robot Snakes Dream like Electric Sheep? Investigating the Effects of Architectural Inductive Biases on Hallucination. - Jerry Huang; Prasanna Parthasarathi; Mehdi Rezagholizadeh; Boxing Chen; Sarath Chandar (ACL (Findings), 2025)

A Generalist Hanabi Agent. - Arjun Vaithilingam Sudhakar; Hadi Nekoei; Mathieu Reymond; Miao Liu; Janarthanan Rajendran; Sarath Chandar (ICLR, 2025)

NeoBERT: A Next Generation BERT. - Lola Le Breton; Quentin Fournier; John Xavier Morris; Mariam El Mezouar; Sarath Chandar (Trans. Mach. Learn. Res., 2025)

Do Large Language Models Know How Much They Know? - Gabriele Prato 001; Jerry Huang; Prasannna Parthasarathi; Shagun Sodhani; Sarath Chandar (CoRR, 2025)

NeoBERT: A Next-Generation BERT. - Lola Le Breton; Quentin Fournier; Mariam El Mezouar; Sarath Chandar (CoRR, 2025)

Steering Large Language Model Activations in Sparse Spaces. - Reza Bayat; Ali Rahimi-Kalahroudi; Mohammad Pezeshki; Sarath Chandar; Pascal Vincent (CoRR, 2025)

TAPNext: Tracking Any Point (TAP) as Next Token Prediction. - Artem Zholus; Carl Doersch; Yi Yang 007; Skanda Koppula; Viorica Patraucean; Xu Owen He; Ignacio Rocco; Mehdi S. M. Sajjadi; Sarath Chandar; Ross Goroshin (CoRR, 2025)

Monitoring morphometric drift in lifelong learning segmentation of the spinal cord. - Enamundram Naga Karthik; Sandrine Bédard; Jan Valosek; Christoph S. Aigner; Elise Bannier; Josef Bednarík; Virginie Callot; Anna J. E. Combes; Armin Curt; Gergely Dávid; Falk Eippert; Lynn Farner; et al. (CoRR, 2025)

Boosting LLM Reasoning via Spontaneous Self-Correction. - Xutong Zhao; Tengyu Xu; Xuewei Wang; Zhengxing Chen; Di Jin; Liang Tan; Yen-Ting; Zishun Yu; Zhuokai Zhao; Yun He; Sinong Wang; Han Fang; et al. (CoRR, 2025)

Did I Faithfully Say What I Thought? Bridging the Gap Between Neural Activity and Self-Explanations in Large Language Models. - Milan Bhan; Jean-Noël Vittaut; Nicolas Chesneau; Sarath Chandar; Marie-Jeanne Lesot (CoRR, 2025)

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. - Mido Assran; Adrien Bardes; David Fan; Quentin Garrido; Russell Howes; Mojtaba Komeili; Matthew J. Muckley; Ammar Rizvi; Claire Roberts; Koustuv Sinha; Artem Zholus; Sergio Arnaud; et al. (CoRR, 2025)

CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design. - Prashant Govindarajan; Davide Baldelli; Jay Pathak; Quentin Fournier; Sarath Chandar (CoRR, 2025)

Optimizers Qualitatively Alter Solutions And We Should Leverage This. - Razvan Pascanu; Clare Lyle; Ionut-Vlad Modoranu; Naima Elosegui Borras; Dan Alistarh; Petar Velickovic; Sarath Chandar; Soham De; James Martens (CoRR, 2025)

Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models. - Istabrak Abbes; Gopeshh Subbaraj; Matthew Riemer; Nizar Islah; Benjamin Thérien; Tsuguchika Tabaru; Hiroaki Kingetsu; Sarath Chandar; Irina Rish (CoRR, 2025)

Parity Requires Unified Input Dependence and Negative Eigenvalues in SSMs. - Behnoush Khavari; Mehran Shakerinava; Jayesh Khullar; Jerry Huang; François Rivest; Siamak Ravanbakhsh; Sarath Chandar (CoRR, 2025)

NovoMolGen: Rethinking Molecular Language Model Pretraining. - Kamran Chitsaz; Roshan Balaji; Quentin Fournier; Nirav Pravinbhai Bhatt; Sarath Chandar (CoRR, 2025)